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Multi-objective grey wolf optimizer for optimal design of switching matrix for shaded pv array dynamic reconfiguration

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dc.citedby44
dc.contributor.authorYousri D.en_US
dc.contributor.authorThanikanti S.B.en_US
dc.contributor.authorBalasubramanian K.en_US
dc.contributor.authorOsama A.en_US
dc.contributor.authorFathy A.en_US
dc.contributor.authorid56688582500en_US
dc.contributor.authorid56267551500en_US
dc.contributor.authorid56654475000en_US
dc.contributor.authorid57194111401en_US
dc.contributor.authorid25654839300en_US
dc.date.accessioned2023-05-29T08:12:07Z
dc.date.available2023-05-29T08:12:07Z
dc.date.issued2020
dc.descriptionDynamic models; Photovoltaic cells; Structural optimization; Current difference; Dynamic reconfiguration process; Multi objective; Multiple local maximums; Optimal structures; Photovoltaic arrays; Shadow phenomena; Switching matrix; Solar power generationen_US
dc.description.abstractOne of the worst negative phenomena faced by photovoltaic (PV) array is the operation under the shadow phenomenon, which significantly affects the generated power. Multiple local maximum power point (MPP) and unique global MPP are generated from the shaded array. Therefore, regular dispersion of the shadow falling on the PV array surface is a vital issue to extract the GMP via reconfiguration of the shaded modules in the array. This article proposes a recent approach based on Multi-objective grey wolf optimizer (MOGWO) to reconfigure the shaded PV array optimally. The main objective of the proposed MOGWO is providing the optimal structure for the switching matrix to minimize the row current difference and maximize the output power. The benefits of the proposed strategy is performing a dynamic reconfiguration process which closes to the reality. The proposed method is validated across 9-9 PV array with six shade patterns. MOGWO schemes results are compared with TCT and modified SuDoKu based on several statistical metrics. The comparison reveals the superiority of MOGWO in tackling the multi-peak issue in the P-V characteristics with harvesting the highest power levels. � 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ACCESS.2020.3018722
dc.identifier.epage159946
dc.identifier.scopus2-s2.0-85097356820
dc.identifier.spage159931
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097356820&doi=10.1109%2fACCESS.2020.3018722&partnerID=40&md5=94596a944802457aff5cafe8d7fa170c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25640
dc.identifier.volume8
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleMulti-objective grey wolf optimizer for optimal design of switching matrix for shaded pv array dynamic reconfigurationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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